一种大尺度二维直线度精密测量的新方法

本文提出了一种远距离、大范围二维直线度测量的新方法．该方法采用特殊设计的十字线准直激光器及线阵CCD，通过特殊的光学系统结构设计，能在0-20m距离内连续测量，直线度范围可达70mm，精度优于0．1mm，实际测量结果表明，该方法可适应野外作业环境。     

从图像的二维谱分析现行电视的缺陷

从图像的二维谱可以得出现行广播电视图像为什么不能满足人眼的视觉匹配以及现行电视制度的不足 ,从而对未来的高清晰度电视发展提出要求。     

二维谐振子与二维氢原子的能量及波函数

借助于ＳＵ(１,１)代数,找出了二维谐振子与二维氢原子的能量及波函数间的关系．     

On the stability preserving property of the double bilinear transformation on a class of 2-D transfer functions

This paper addresses the BIBO (bounded-input bounded-output) stability of a class of discrete 2-D quarter-plane filters in the presence of nonessential singularities of the second kind (NSSK's) on the unit bidisk. Conditions under which the double bilinear transformation (DBT) preserves stability are derived. The results presented here also extend the class of systems whose stability can be predicted. Use of the inverse DBT to produce a continuous equivalent of the discrete 2-D transfer function allows easy application of a continuous-domain equivalent of a criterion developed by Dautov. The necessary and sufficient condition for stability derived in this work provides a simple check for the class of systems under consideration. From this class of systems, it is also possible to construct stable pairs of mutually inverse transfer functions.     

Formation of uniform GaAs multi-atomic steps with 20–30 nm periodicity and related structures on vicinal (111)B planes by MBE

We studied morphology of GaAs surfaces and the transport properties of two-dimensional electron gas (2DEG) on vicinal (111)B planes. Multi-atomic steps (MASs) are found on the vicinal (111)B facet grown by molecular beam epitaxy, which will affect electron transport on the facet. We also studied how the morphology of GaAs epilayers on vicinal (111)B substrates depends on growth conditions, especially on the As₄ flux. The uniformity of MASs on the substrates have been improved and smooth surfaces were obtained when the GaAs was grown with high As₄ flux, providing step periodicity of 20 nm. The channel resistance of the 2DEG perpendicular to the MASs is reduced drastically with this smooth morphology. These findings are valuable not only for fabricating quantum devices on the (111)B facets but also those on the vicinal (111)B substrates.     

Monitoring Proteolysis During Cheddar Cheese Ripening Using Two-Dimensional Gel Electrophoresis

A 2-D gel electrophoretic method, consisting of isoelectric focusing and alkaline urea-PAGE was used to monitor proteolysis during ripening (180d, 5°C and 8°C) of full- and reduced-fat Cheddar cheese. The method enabled quantifying changes in levels of peptides in cheese with good spot-resolution. Results can complement those from other analyses, especially those for determining low MW peptides. Notable effects were found for cheese composition and ripening temperature on gel pattern and on relative levels of selected proteolysis products. In both cheese varieties, most peptides reached a maximum during the first 3 ripening months and gradually disappeared as ripening advanced.     

MECHANISM OF SOUND GENERATION BY FLOW OVER TWO CAVITIES IN TWO DIMENSIONS

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多分量调频信号的阵列处理时频交叉项的抑制方法

在应用时频-MUSIC方法对多分量调频信号进行到达角估计的问题中,针对时频分布中交叉项的存在对估计性能的影响,提出了一种基于阵列信号处理抑制时频分布交叉项的新方法。该方法利用多信源在各阵元上的延迟对时频分布交叉项振荡相位的影响,联合运用多通道信号处理和图像处理的方法,采用二维乘法滤波,减小高频振荡交叉项在时频图像中的占据区域,从而达到抑制交叉项的目的。仿真实验显示该方法具有良好的效果。     

紧扣内存变量关系巧解矩阵类问题

C语言学习过程中,不少初学者不能建立思维的模型,无法将形象可行的矩阵运算、旋转事件抽象化成算法语言。讲解了指导学生掌握矩阵操作算法的推导方法。     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.